Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction

Barbara Schormair; Chen Zhao; Steven Bell; Maria Didriksen; Muhammad Nawaz; Nathalie Schandra; Ambra Stefani; Birgit Högl; Yves Dauvilliers; Cornelius Bachmann; David Kemlink; Karel Sonka; Walter Paulus; Claudia Trenkwalder; Wolfgang Oertel; Magdolna Hornyak; Maris Teder-Laving; Andres Metspalu; Georgios Hadjigeorgiou; Olli Polo; Ingo Fietze; Owen Ross; Zbigniew Wszolek; Abubaker Ibrahim; Melanie Bergmann; Volker Kittke; Philip Harrer; Joseph Dowsett; Sofiene Chenini; Sisse Rye Ostrowski; Erik Sørensen; Christian Erikstrup; Ole Pedersen; Mie Topholm Bruun; Kaspar Nielsen; Adam Butterworth; Nicole Soranzo; Willem Ouwehand; David Roberts; John Danesh; Brendan Burchell; Nicholas Furlotte; Priyanka Nandakumar; Amélie Bonnefond; Louis Potier; Christopher Earley; William Ondo; Lan Xiong; Alex Desautels; Markus Perola; Pavel Vodicka; Christian Dina; Monika Stoll; Andre Franke; Wolfgang Lieb; Alexandre Stewart; Svati Shah; Christian Gieger; Annette Peters; David Rye; Guy Rouleau; Klaus Berger; Hreinn Stefansson; Henrik Ullum; Kari Stefansson; David Hinds; Emanuele Di Angelantonio; Konrad Oexle; Juliane Winkelmann

doi:10.1038/s41588-024-01763-1

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Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction

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Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction

Barbara Schormair, Chen Zhao, Steven Bell, Maria Didriksen, Muhammad Nawaz, Nathalie Schandra, Ambra Stefani, Birgit Högl, Yves Dauvilliers, Cornelius Bachmann, …

Nature Genetics, Vol.56(6), pp.1090-1099

05/06/2024

DOI: https://doi.org/10.1038/s41588-024-01763-1

Abstract

Abstract Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes ( r g = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongenetic information performed best in risk prediction (area under the curve (AUC) = 0.82–0.91). In summary, we identified targets for drug development and repurposing, prioritized potential causal relationships between RLS and relevant comorbidities and risk factors for follow-up and provided evidence that nonlinear interactions are likely relevant to RLS risk prediction.

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Title: Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction
Creators - without role: Barbara Schormair - Helmholtz Zentrum München
Chen Zhao - Helmholtz Zentrum München
Steven Bell - University of Cambridge
Maria Didriksen - Copenhagen University Hospital
Muhammad Nawaz - deCODE Genetics
Nathalie Schandra - Helmholtz Zentrum München
Ambra Stefani - Innsbruck Medical University
Birgit Högl - Innsbruck Medical University
Yves Dauvilliers - Université de Montpellier, Institut des Neurosciences de Montpellier - INM
Cornelius Bachmann
David Kemlink - Charles University
Karel Sonka - Charles University
Walter Paulus - Ludwig-Maximilians-Universität München
Claudia Trenkwalder - Paracelsus Elena Klinik Kassel
Wolfgang Oertel - Helmholtz Zentrum München
Magdolna Hornyak
Maris Teder-Laving - University of Tartu
Andres Metspalu - University of Tartu
Georgios Hadjigeorgiou - University of Cyprus
Olli Polo
Ingo Fietze - Charité - Universitätsmedizin Berlin
Owen Ross - Mayo Clinic in Florida
Zbigniew Wszolek
Abubaker Ibrahim - Universität Innsbruck
Melanie Bergmann - Innsbruck Medical University
Volker Kittke - Technical University of Munich
Philip Harrer - Technical University of Munich
Joseph Dowsett - Copenhagen University Hospital
Sofiene Chenini - Inserm
Sisse Rye Ostrowski - Copenhagen University Hospital
Erik Sørensen - Copenhagen University Hospital
Christian Erikstrup - Aarhus University Hospital
Ole Pedersen - University of Copenhagen
Mie Topholm Bruun
Kaspar Nielsen - Aalborg University Hospital
Adam Butterworth - University of Cambridge
Nicole Soranzo - National Institute for Health Research
Willem Ouwehand - University of Cambridge
David Roberts - National Institute for Health Research
John Danesh - British Heart Foundation
Brendan Burchell
Nicholas Furlotte - 23andMe
Priyanka Nandakumar - 23andMe
Amélie Bonnefond - European Genomic Institute for Diabetes
Louis Potier - Institut Necker Enfants Malades
Christopher Earley - Johns Hopkins University
William Ondo - Cornell University
Lan Xiong - Montreal Neurological Institute and Hospital
Alex Desautels - Hôpital du Sacré-Cœur de Montréal
Markus Perola - University of Helsinki
Pavel Vodicka - Czech Academy of Sciences
Christian Dina - Inserm
Monika Stoll - University of Münster
Andre Franke - Kiel University
Wolfgang Lieb - Kiel University
Alexandre Stewart
Svati Shah - Duke University
Christian Gieger - Helmholtz Zentrum München
Annette Peters - Helmholtz Zentrum München
David Rye - Emory University
Guy Rouleau - McGill University
Klaus Berger - University of Münster
Hreinn Stefansson - deCODE Genetics
Henrik Ullum - Statens Serum Institut
Kari Stefansson
David Hinds - 23andMe
Emanuele Di Angelantonio - University of Cambridge
Konrad Oexle - Helmholtz Zentrum München
Juliane Winkelmann - Munich Cluster for Systems Neurology
Publication Details: Nature Genetics, Vol.56(6), pp.1090-1099
Identifiers: 9939716509311
Academic Unit: Institut des Neurosciences de Montpellier - INM
Language: English
Resource Type: Journal article
Local Fields: hal-04965474